What are Large Language Models and Their Main Tasks?

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Large language models are software that operate as huge databases of probabilities. They perform four main tasks: generation, summarization, rewriting, and transformation. In generation, they can produce text based on a given prompt. Summarization involves condensing a large text into a shorter version. Rewriting means altering the original text. Transformation involves converting one type of text into another. These models excel in generation, summarization, rewriting, and transformation. They are particularly good at transforming one thing into another due to their design as transformers. However, when starting with simple prompts, the initial output may be basic and elementary.

This week I’m excited to bring you this informative and topical conversation I had with Christopher S. Penn about the realities, myths, and dare I say productivity applications within ChatGPT and similar language based software tools which I'm sure you have noticed are getting more and more attention in the realms of social media, tech chatter, and even politics.

I’ve known Christopher for years and I can’t think of anyone more qualified to guide me and you through this topic. Christopher bridges the gap between marketing and technology. What he shares on social media and writes about helps you understand marketing and technology better plus he is a better coder than most marketers, and a better marketer than most coders. By having one foot in both worlds, he finds solutions that work in one place and brings them to the other. Christopher speaks publicly about digital marketing, marketing technology, and machine learning/artificial intelligence. He is the co-founder of Trust Insights, a data analytics company focused on helping you make more money with your data, a co-founder of PodCamp with Chris Brogan, and co-host of the Marketing Over Coffee marketing podcast with John Wall.

In this chat Christopher breaks down the real world applications of ChatGPT while explaining its limitations and ways to maximize the effectiveness of the tool. We discuss some of the ethical and political concerns swirling around the technology while dispelling some of the more hysterical myths that have been propagated online and in print. Regardless of your familiarity with this technology this is a great primer for understanding and maximizing these tools for a wide range of both creative, and labor intensive tasks.

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